• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.107-120
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• 2020

In a performance-based evaluation of structures in use, the current performance is assessed by summing up the weighting of the evaluation indices for each performance. In this study, to suggest a performance-based evaluation technique for NATM tunnels in use, the performance evaluation indices were derived by examining the characteristics and similarities of each index developed from previous study. The weighting of the evaluation indices was derived by calculating the relative importance of each evaluation indices from the AHP analysis. In order to develop a quantitative evaluation model, grading criteria for each performance index was derived through literature review, and performance evaluation tables for road and railway tunnels were presented. In order to verify the significance of the proposed performance evaluation model, the correlation analysis was performed between each evaluation index and the final evaluation result. In the correlation analysis, the survey data measured through precision safety diagnosis in the tunnel in use was applied. It may be said that the proposed evaluation indices, weighting, criteria and evaluation models for tunnels in use can be applied to the performance-based maintenance system of tunnels.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.802-810
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• 2006

For a thorough train control, the precise train position detection is necessarily required. The widely used current way for train position detection is the one of using track circuits. The track circuit has a simple structure, and has a high level of reliability. However trains can be detected only on track circuits, which have to be installed on all ground sections, and much amount of cost for its installation and maintenance is needed. In addition, for the track circuit, only discontinuous position detection is possible because of the features of the closed circuit loop configuration. As the recent advances in telecommunication technologies and high-tech vehicle-based control equipments, for the train position detection, the method to detect positions directly from on trains is being studied. Vehicle-based position detection method is to estimate train positions, speed, timing data continuously, and to use them as the control information. In this paper, the features of GPS navigation and DR navigation are analyzed, and the navigation filters are designed by constructing vehicle-based train position detection method by combining GPS navigation and DR navigation for their complementary cooperation, and by using kalman filter. The position estimation performance of the proposed method is also confirmed by simulations.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.398-409
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• 2021

Background: The types and effects of hazardous pollutants in indoor air may vary depending on the characteristics of the sources and pollutants caused by physical and chemical properties of buildings, the influence of outdoor air, and the exposure and use characteristics of residents. Objectives: This study was conducted to provide basic data on the establish of indoor air quality management for different classes of public-use facilities by presenting the characteristics of concentration distribution of hazardous pollutants by different public-use facilities and the status of the excess proportion of exceeding standards. Methods: This study analyzed self-measurement data from public-use facilities taken from 2017 to 2019 A total of 133,525 facilities were surveyed. A total of 10 types of pollutants that have maintenance and recommended standards stipulated in the Indoor Air Quality Control Act from the Ministry of Environment were investigated. The excess proportion and the substances exceeding the criteria for each type of public-use facilities for these pollutants were investigated. Results: As a result of the analysis of the proportion of exceeding the standard for each type of public-use facility, the facilities with the highest excess proportion of the standards for each hazardous pollutant were: PM₁₀ in railway stations (8.93%), PM_2.5 in daycare centers (7.36%), CO₂ in bus terminals (2.37%), HCHO in postpartum care centers (4.11%), total airborne bacteria in daycare centers (0.69%), CO in museums (0.1%), NO₂ in postpartum care centers (1.15%), Rn in museums (0.78%), total volatile organic compounds in postpartum care centers (7.20%) and mold in daycare centers (1.44%). Conclusions: Although uncertainty may arise because this study is a result of self-measurement, it is considered that this study has significance for providing basic data on the establishment in the future of indoor air quality management measures customized for each type of public-use facility.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.353-362
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• 2023

In this research, the usage status and characteristics of user big data of Mobike, a dockless bike sharing service introduced in Suwon city, were analyzed, and multiple regression analysis was performed to identify factors influencing the demand for dockless bike sharing service. For analysis, usage data of bike sharing system in Suwon city in 2019 were obtained, and they were organized by areas. As a result of analyzing the characteristics of the influencing factors selected for each area, it was found that the extension of bicycle roads shows high in areas with high demand for bicycles or adjacent areas. Also, the population of 10-30's shows high in areas with high demand for bicycles or adjacent areas. In addition, it was analyzed that the use of bike sharing system is high in areas with high maintenance rate of bicycle roads and large-scale residential and commercial facilities near residential districts and adjacent areas. As a result of the multiple regression analysis, it is analyzed that length of bicycle·pedestrian roads (non-separated), population of 10-30's, number of railway stations, number of schools, number of commercial facilities, number of industrial facilities factors were significant. It is expected that it may be possible to create an environment in which citizens want to use dockless bike sharing service by identifying factors affecting the number of stationless shared bicycles. Also, the results of data analysis are considered to be contributing to policy data to promote the use of dockless bike sharing.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.517-528
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• 2007

Domestic or international existing researches regarding rail damage factors are focused on laying, vehicle conditions, driving speed and driving habits and overlook characteristics of track structure (elasticity, maintenance etc). Also in ballast track, as there is no special lateral spring stiffness of track also called as ballast lateral resistance in concrete track, generally, existing study shows concrete track has 2 time shorter life cycle for rail replacement than ballast track due to abrasion. As a result of domestic concrete track design and operation performance review, concrete track elasticity is lower than track elasticity of ballast track resulting higher damage on rail and tracks. Generally, concrete track has advantage in track elasticity adjustment than ballast track and in case of Europe, in concrete track design, it is recommended to have same or higher performance range of vertical elastic stiffness of ballast track but domestically or internationally review on lateral spring stiffness of track is very minimal. Therefore, through analysis of service line track on site measurement and analysis on performance of maintenance, in this research, dynamic characteristic behaviors of commonly used ballast and concrete track are studied to infer elasticity of service line track and experimentally prove effects of track lateral spring stiffness that influence curved rail damage as well as correlation between track elasticity by track system and rail damage to propose importance of appropriate elastic stiffness level for concrete and ballast track.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.113-132
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• 2003

Using nonradial data envelopment analysis(DEA) under assumptions of strong disposability and variable returns scale, this paper annually estimates productive. technical and allocative efficiencies of three publicly-owned rail transit properties which are different in terms of organizational type: Seoul Subway Corporation(SSC, local public corporation), the Seoul Metropolitan Electrified Railways sector (SMESRS) of Korea National Railroad(the national railway operator controlled by the Ministry of Construction and Transportation(MOCT)), and Busan Urban Transit Authority (BUTA, the national authority controlled by MOCT). Using the estimation results of Tobit regression analysis. the paper next computes their true productive, true technical and true allocative efficiencies, which reflect only the impacts of internal factors such as production activity by removing the impacts of external factors such as an organizational type and a track utilization rate. And the paper also computes an organizational efficiency and annually gross efficiencies for each property. The paper then conceptualized that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car & maintenance and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results obtained from DEA show that, on an average, SSC is the most efficient property on the productive and allocative sides, while SMESRS is the most technically-efficient one. On the other hand. BUTA is the most efficient one on the truly-productive and allocative sides, while SMESRS on the truly-technical side. Another important result is that the differences in true efficiency estimates among the three properties are considerably smaller than those in efficiency estimates. Besides. the most cost-efficient organizational type appears to be a local public corporation represented by SSC, which is also the most grossly-efficient property. These results suggest that a measure to sort out the impacts of external factors on the efficiency of rail transit properties is required to assess fairly it, and that a measure to restructure (establish) an existing(a new) rail transit property into a local public corporation(or authority) is required to improve its cost efficiency.